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A post-CM infrastructure
delivery pipeline
… or why I'm here to learn more
@beddari at @cfgmgmtcamp
Problem statement
We were using CM tooling but
NOT WINNING
What we had built with love -
√ automated tests
√ JEOS + baseline + role
√ monitoring across envs
- was a total failure!
√ non-manageable rebuild times
√ envs were starting to “leak”
√ upgrades were high risk
“Our systems are ...
eventually repeatable”
Darn it, test that small change in prod
People told us
“CLEARLY
you are doing something wrong”
docker docker docker docker docker docker
docker docker docker docker docker docker
docker docker docker docker docker
Solution:
We stopped doing
configuration management
input | change | output
input
Inputs are typically managed artifacts
Repos, packages, images, containers
change
Feed input to Packer which in turn runs a
builder that applies change,
producing output
output
A versioned artifact, suitable for consumption
or further processing
Repos, packages, images, containers
Abstraction
is key
A input-change-output chain is a project
●
A project is versioned in git
●
Artifacts are testable
Your new job is ...
describing state to produce artifacts
and keeping that state from drifting
We didn't throw it all out
A system consists of 1+N roles,
a role consists of 1+N profiles.
First lesson learned
Think about managing state,
where do you want it?
https://github.com/Nubisproject/nubis-docs/blob/mas...
Abstraction is future proofing
http://jerakia.io
“Decoupled from any particular configuration
management system”
Does it work?
YES
Packer with masterless Puppet
Terraform and Ansible to deploy and replace
Masterless Puppet to audit and correct drift...
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A post-CM infrastructure delivery pipeline

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Ignite talk at Cfgmgmtcamp 2016

Youtube: https://www.youtube.com/watch?v=2h-W8s6sFaw

Publicada em: Engenharia
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A post-CM infrastructure delivery pipeline

  1. 1. A post-CM infrastructure delivery pipeline … or why I'm here to learn more @beddari at @cfgmgmtcamp
  2. 2. Problem statement We were using CM tooling but NOT WINNING
  3. 3. What we had built with love - √ automated tests √ JEOS + baseline + role √ monitoring across envs
  4. 4. - was a total failure! √ non-manageable rebuild times √ envs were starting to “leak” √ upgrades were high risk
  5. 5. “Our systems are ... eventually repeatable” Darn it, test that small change in prod
  6. 6. People told us “CLEARLY you are doing something wrong”
  7. 7. docker docker docker docker docker docker docker docker docker docker docker docker docker docker docker docker docker
  8. 8. Solution: We stopped doing configuration management
  9. 9. input | change | output
  10. 10. input Inputs are typically managed artifacts Repos, packages, images, containers
  11. 11. change Feed input to Packer which in turn runs a builder that applies change, producing output
  12. 12. output A versioned artifact, suitable for consumption or further processing Repos, packages, images, containers
  13. 13. Abstraction is key
  14. 14. A input-change-output chain is a project ● A project is versioned in git ● Artifacts are testable
  15. 15. Your new job is ... describing state to produce artifacts and keeping that state from drifting
  16. 16. We didn't throw it all out A system consists of 1+N roles, a role consists of 1+N profiles.
  17. 17. First lesson learned Think about managing state, where do you want it? https://github.com/Nubisproject/nubis-docs/blob/master/MANIFESTO.md
  18. 18. Abstraction is future proofing http://jerakia.io “Decoupled from any particular configuration management system”
  19. 19. Does it work?
  20. 20. YES Packer with masterless Puppet Terraform and Ansible to deploy and replace Masterless Puppet to audit and correct drift Single YAML configuration data store yum upgrade considered harmful

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